{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:O6J76X2MNWZUSE7N5OAV3W2VTZ","short_pith_number":"pith:O6J76X2M","schema_version":"1.0","canonical_sha256":"7793ff5f4c6db34913edeb815ddb559e494440a306a46d758c3c6ac188c6f7af","source":{"kind":"arxiv","id":"2605.23986","version":1},"attestation_state":"computed","paper":{"title":"MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.MA"],"primary_cat":"cs.DB","authors_text":"Bingsheng He, Han Chen, Hongbao Zhang, Jason Zeng, Michael Heinrich, Ming Wu, Wei Wu, Wenqi Pei, Zining Zhang","submitted_at":"2026-05-16T13:11:47Z","abstract_excerpt":"Memory is a fundamental component for enabling long-context LLM agents, supporting persistent state across interactions through a continuous serve-and-update lifecycle. Despite substantial prior work, existing systems suffer from significant maintenance overhead due to two key limitations: coarse-grained state management and inherently sequential update pipelines. In particular, updates are often tightly coupled with LLM inference and require full-state rewrites, leading to poor scalability and growing latency as memory accumulates. To address these challenges, we present MemForest, a memory f"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.23986","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DB","submitted_at":"2026-05-16T13:11:47Z","cross_cats_sorted":["cs.AI","cs.MA"],"title_canon_sha256":"5ccbbef404abd004552fbd5c295e3eadd22666c6e742a6495d6a9b942db1d4b5","abstract_canon_sha256":"0a91d4fa83f859df6e32ba8f99b85c18806df9341a9037311bd2fb7b6e66c4af"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T01:02:39.251499Z","signature_b64":"JDEoo8N3hSEYegGpq60I83tOUkyUhJtEvsKbGpRUIlkmuB1svKg8IZklU0eqWNQLVnqNZypjequgxhteB9WSAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7793ff5f4c6db34913edeb815ddb559e494440a306a46d758c3c6ac188c6f7af","last_reissued_at":"2026-05-26T01:02:39.250638Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T01:02:39.250638Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.MA"],"primary_cat":"cs.DB","authors_text":"Bingsheng He, Han Chen, Hongbao Zhang, Jason Zeng, Michael Heinrich, Ming Wu, Wei Wu, Wenqi Pei, Zining Zhang","submitted_at":"2026-05-16T13:11:47Z","abstract_excerpt":"Memory is a fundamental component for enabling long-context LLM agents, supporting persistent state across interactions through a continuous serve-and-update lifecycle. Despite substantial prior work, existing systems suffer from significant maintenance overhead due to two key limitations: coarse-grained state management and inherently sequential update pipelines. In particular, updates are often tightly coupled with LLM inference and require full-state rewrites, leading to poor scalability and growing latency as memory accumulates. To address these challenges, we present MemForest, a memory f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.23986","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.23986/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.23986","created_at":"2026-05-26T01:02:39.250791+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.23986v1","created_at":"2026-05-26T01:02:39.250791+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.23986","created_at":"2026-05-26T01:02:39.250791+00:00"},{"alias_kind":"pith_short_12","alias_value":"O6J76X2MNWZU","created_at":"2026-05-26T01:02:39.250791+00:00"},{"alias_kind":"pith_short_16","alias_value":"O6J76X2MNWZUSE7N","created_at":"2026-05-26T01:02:39.250791+00:00"},{"alias_kind":"pith_short_8","alias_value":"O6J76X2M","created_at":"2026-05-26T01:02:39.250791+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/O6J76X2MNWZUSE7N5OAV3W2VTZ","json":"https://pith.science/pith/O6J76X2MNWZUSE7N5OAV3W2VTZ.json","graph_json":"https://pith.science/api/pith-number/O6J76X2MNWZUSE7N5OAV3W2VTZ/graph.json","events_json":"https://pith.science/api/pith-number/O6J76X2MNWZUSE7N5OAV3W2VTZ/events.json","paper":"https://pith.science/paper/O6J76X2M"},"agent_actions":{"view_html":"https://pith.science/pith/O6J76X2MNWZUSE7N5OAV3W2VTZ","download_json":"https://pith.science/pith/O6J76X2MNWZUSE7N5OAV3W2VTZ.json","view_paper":"https://pith.science/paper/O6J76X2M","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.23986&json=true","fetch_graph":"https://pith.science/api/pith-number/O6J76X2MNWZUSE7N5OAV3W2VTZ/graph.json","fetch_events":"https://pith.science/api/pith-number/O6J76X2MNWZUSE7N5OAV3W2VTZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/O6J76X2MNWZUSE7N5OAV3W2VTZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/O6J76X2MNWZUSE7N5OAV3W2VTZ/action/storage_attestation","attest_author":"https://pith.science/pith/O6J76X2MNWZUSE7N5OAV3W2VTZ/action/author_attestation","sign_citation":"https://pith.science/pith/O6J76X2MNWZUSE7N5OAV3W2VTZ/action/citation_signature","submit_replication":"https://pith.science/pith/O6J76X2MNWZUSE7N5OAV3W2VTZ/action/replication_record"}},"created_at":"2026-05-26T01:02:39.250791+00:00","updated_at":"2026-05-26T01:02:39.250791+00:00"}